MenuMate

• 

  main page

• 

  second page

With an increase in the number of fast food and fine dining restaurants in the recent years, the number of restaurants that have begun to mal-perform has risen at an equivalent rate. Due to either a lack of dedication to their business, or an issue revolving company finances, certain fast food restaurants and fine dining companies may not be at their operational prime.

This decrease in dining experience would result in you, their valued guests, to be offered subpar service and potentially hazardous and life-threatening food in return.

Our project, MenuMate, helps to avert this issue as much as possible, so that any customer who pays for their food are offered a quality product that is safe and delicious. through one simple search, users will be able to look for their favourite restaurants and determine whether or not their favourite restaurants shouldn’t be there favourite anymore!

By analyzing a variety of indicators, such as Health inspection records, food-site reviews, and a variety of other offically-recognized indicators, MenuMate is able to determine whether or not your restaurant is properly producing quality food in a safe and ethical manner.

Though MenuMate is only available in the city of Ottawa, we hope to branch out our project to various other cities to make sure that everyone is able to receive the great food that they deserve!

We built this using a React frontend and a Flask backend.

One challenge we ran into was linking all the frameworks together to ensure our product was functioning as it should be. We are also all relatively new to hackathons and so we lacked a lot of experience regarding a lot of the technologies. Finally, we tried incorporating a database to store the data but it became too tall of a task and so we stuck to storing the data into a .csv file.

We're proud that we were able to successfully link the frontend and backend through API calls and our use of Flask. Also, the conversion between our Figma design and our React frontend was pretty impressive considering it was our first time using both.

We learned a lot more about backend and in general how to develop a fullstack application and its requirements.

We're hoping to expand the dataset such that it includes more than the first 50 restaurants taken from the database. We also hope to successfully incorporate MongoDB to store this future data.

Built With

• beautiful-soup
• co:here
• css
• figma
• flask
• html
• javascript
• python
• react
• rest